Effect of a Myopia Prediction System on Myopia Prevention and Control

Impact of Feedback Based on the Myopia Prediction System on High Myopia Risk and Consultation Behavior in School-aged Children: a Cluster Randomized Controlled Trial

The global rise in myopia, particularly among children and adolescents in China, underscores the inadequacy of current prevention strategies, indicating that conventional screening and education alone are insufficient to curb the prevalence. Integrating personalized myopia prediction into routine care may enhance risk awareness, promote proactive prevention, and improve adherence to medical advice, ultimately reducing the future burden of high myopia.

A myopia prediction system based on artificial intelligence was previously developed, accurately predicting future high myopia risk using efficient, robust, and easily accessible predictive factors, including age, spherical equivalent, and the annual progression of spherical equivalent. This study aims to conduct a prospective, one-year, cluster randomized controlled clinical trial to investigate the effectiveness of this prediction system in preventing and controlling myopia in school-aged children.

Inclusion Criteria:

• The participant and their guardian voluntarily signed the informed consent form
• Has the record of eye refraction examination in the past year
• Aged 9 to 11 years, regardless of gender

Exclusion Criteria:

• High myopia(spherical equivalent ≤ -6.00 D)
• Ocular diseases other than myopia (e.g., strabismus, amblyopia, congenital cataract, juvenile glaucoma, retinal diseases).
• Systemic diseases that may affect vision or visual development (e.g., diabetes or other endocrine disorders, cardiovascular or respiratory diseases, Down syndrome)